Deep learning based phase retrieval in quantitative phase microscopy

2020 ◽  
Author(s):  
Yao Ye ◽  
Xin Shu ◽  
Renjie Zhou
Keyword(s):  
Deep Learning ◽  
Phase Retrieval ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy

New Progress on Quantitative Phase Microscopy and Phase Retrieval for Biological Cells

2014 ◽  
Vol 51 (2) ◽  
pp. 020006
Author(s):  
徐媛媛 Xu Yuanyuan ◽  
王亚伟 Wang Yawei ◽  
金卫凤 Jin Weifeng ◽  
季颖 Ji Ying ◽  
张力 Zhang Li ◽  
...  
Keyword(s):  
Phase Retrieval ◽  
Biological Cells ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy

scholarly journals PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning

2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Yair Rivenson ◽  
Tairan Liu ◽  
Zhensong Wei ◽  
Yibo Zhang ◽  
Kevin de Haan ◽  
...  
Keyword(s):  
Deep Learning ◽  
Label Free ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy ◽  
Microscopy Images

scholarly journals Characterization of Liposomes Using Quantitative Phase Microscopy (QPM)

Pharmaceutics ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 590
Author(s):  
Jennifer Cauzzo ◽  
Nikhil Jayakumar ◽  
Balpreet Singh Ahluwalia ◽  
Azeem Ahmad ◽  
Nataša Škalko-Basnet
Keyword(s):  
Rapid Development ◽  
Fluorescent Labeling ◽  
Label Free ◽  
Batch Mode ◽  
Full Field ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy ◽  
Tracking Ability

The rapid development of nanomedicine and drug delivery systems calls for new and effective characterization techniques that can accurately characterize both the properties and the behavior of nanosystems. Standard methods such as dynamic light scattering (DLS) and fluorescent-based assays present challenges in terms of system’s instability, machine sensitivity, and loss of tracking ability, among others. In this study, we explore some of the downsides of batch-mode analyses and fluorescent labeling, while introducing quantitative phase microscopy (QPM) as a label-free complimentary characterization technique. Liposomes were used as a model nanocarrier for their therapeutic relevance and structural versatility. A successful immobilization of liposomes in a non-dried setup allowed for static imaging conditions in an off-axis phase microscope. Image reconstruction was then performed with a phase-shifting algorithm providing high spatial resolution. Our results show the potential of QPM to localize subdiffraction-limited liposomes, estimate their size, and track their integrity over time. Moreover, QPM full-field-of-view images enable the estimation of a single-particle-based size distribution, providing an alternative to the batch mode approach. QPM thus overcomes some of the drawbacks of the conventional methods, serving as a relevant complimentary technique in the characterization of nanosystems.

scholarly journals Efficient quantitative phase microscopy using programmable annular LED illumination

2017 ◽  
Vol 8 (10) ◽  
pp. 4687 ◽  
Author(s):  
Jiaji Li ◽  
Qian Chen ◽  
Jialin Zhang ◽  
Yan Zhang ◽  
Linpeng Lu ◽  
...  
Keyword(s):  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy

Direct full compensation of the aberrations in quantitative phase microscopy of thin objects by a single digital hologram

2007 ◽  
Vol 90 (4) ◽  
pp. 041104 ◽  
Author(s):  
L. Miccio ◽  
D. Alfieri ◽  
S. Grilli ◽  
P. Ferraro ◽  
A. Finizio ◽  
...  
Keyword(s):  
Quantitative Phase ◽  
Digital Hologram ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy ◽  
Full Compensation

scholarly journals Imaging red blood cell dynamics by quantitative phase microscopy

2008 ◽  
Vol 41 (1) ◽  
pp. 10-16 ◽  
Author(s):  
Gabriel Popescu ◽  
YoungKeun Park ◽  
Wonshik Choi ◽  
Ramachandra R. Dasari ◽  
Michael S. Feld ◽  
...  
Keyword(s):  
Blood Cell ◽  
Red Blood Cell ◽  
Cell Dynamics ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy
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